Visium
Human breast
human-breast-cancer-whole-transcriptome-analysis-1-standard-1-2-0
silver Interactive viewer H&E Invasive Lobular Carcinoma No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'Parent_Visium_Human_BreastCancer_full_image': DataTree[cyx] (3, 24240, 24240), (3, 12120, 12120), (3, 6060, 6060), (3, 3030, 3030), (3, 1515, 1515)
│ ├── 'Parent_Visium_Human_BreastCancer_hires_image': DataArray[cyx] (3, 2000, 2000)
│ └── 'Parent_Visium_Human_BreastCancer_lowres_image': DataArray[cyx] (3, 600, 600)
├── Shapes
│ └── 'Parent_Visium_Human_BreastCancer': GeoDataFrame shape: (4325, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4325, 36601)
with coordinate systems:
▸ 'Parent_Visium_Human_BreastCancer', with elements:
Parent_Visium_Human_BreastCancer_full_image (Images), Parent_Visium_Human_BreastCancer_hires_image (Images), Parent_Visium_Human_BreastCancer_lowres_image (Images), Parent_Visium_Human_BreastCancer (Shapes)
▸ 'Parent_Visium_Human_BreastCancer_downscaled_hires', with elements:
Parent_Visium_Human_BreastCancer_hires_image (Images), Parent_Visium_Human_BreastCancer (Shapes)
▸ 'Parent_Visium_Human_BreastCancer_downscaled_lowres', with elements:
Parent_Visium_Human_BreastCancer_lowres_image (Images), Parent_Visium_Human_BreastCancer (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("A54P3QWEIAUEuAa3") # latest version
sdata = artifact.load() # cache, then load into memory
group = artifact.open() # stream without downloading
path = artifact.cache() # sync into the local cache, returns the path Load from the CLI
# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/A54P3QWEIAUEuAa3
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid A54P3QWEIAUEuAa3 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["A54P3QWEIAUEuAa30000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- Visium
- Organism
- human
- Tissue
- breast
- Condition
- Invasive Lobular Carcinoma
- Modality
- RNA
- Observations
- 4,325
- Tier
- silver
- Chemistry
- Visium v1
- Magnification
- 20x
- Resolution
- 24,240 × 24,240 px
- mpp
- 0.310 µm/px
- Size
- 1.6 GB
- Sample ID
- human-breast-cancer-whole-transcriptome-analysis-1-standard-1-2-0
- License
- CC BY 4.0
- Published
- Oct 27, 2020
Cite this dataset
No linked publication found — please cite the data source: 10x Genomics ↗.
Source: 10x Genomics ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB